Particle motion affects microscopic momentum, heat/mass transfers, and macroscopic mixing/separation performances in engineering processes ranging from those involving granular flows to multiphase systems. The primary interests of researchers seeking to improve the performances of such processes are finding the best ways to understand particle motion. Several methods have been developed to understand particle motion, among which radiation-based techniques have shown particular advantages because they can non-invasively investigate dynamic particle motion. This article reviews four prominent radiation-based techniques for studying particle motion, including Radioactive Particle Tracking (RPT), Positron Emission Particle Tracking (PEPT), X-ray-based methods and Magnetic Resonance Imaging (MRI). The principles and characteristics of these techniques are explained, and recent advances and applications are reviewed.

Rapid development of antibiotic resistance in pathogenic bacteria and a decline in the pharmaceutical development of new antibiotics are pushing the research community to explore alternative antimicrobials that can replace or complement antibiotics. Bacteriophages (or, phages) are naturally occurring viruses that can kill bacteria with high specificity and can evolve to target resistant bacteria. Phages have been historically employed as antimicrobial agents, but they were overshadowed by the emergence of antibiotics. With a renewed focus on phages, it is important to study their clinical efficacy, safety, and formulation. Pulmonary infections have a large burden of global morbidity and frequently involve multidrug-resistant pathogens such as Acinetobacter baumannii, Klebsiella pneumoniae, Mycobacterium tuberculosis, and Pseudomonas aeruginosa. Therefore, this can be an important area of application of phages. Dry powder inhalers can be an effective strategy to deliver phages to the lungs because they are easy-to-use, portable, and capable of delivering a higher lung dose than oral or intravenous route. They also have longer shelf life and lower cold storage requirements than solutions. Therefore, the aim of the current review is to summarize recent findings on bacteriophage dry powder formulations, particularly focusing on the effect of various excipients and manufacturing factors on phage titer preservation.

Fugitive particulate matter (FPM) refers to a mixture of solid particles and liquid droplets that are released into the air without passing through confined flow equipment. These emissions of FPM can originate from natural processes and anthropogenic activities. FPM emissions are an important source of PM2.5. Precisely measuring the size, concentration, and other properties of such particulate matter is crucial for effectively controlling emission sources and improving air quality. However, compared with particulate matter emission from stationary sources, it is difficult to monitor the FPM effectively owing to its dispersive and irregular emissions. Traditional measuring methods for FPM are based on sampling, which is a point monitoring approach and can be time-consuming. In recent years, several new techniques based on optical principles, image-based processes and low-cost sensors have been developed and applied for FPM measurement, with the advantages of spatial and time resolutions. The current state and future development of FPM measurements are reviewed in this paper.

The 54th Symposium on Powder Technology organized by Hosokawa Powder Technology Foundation took place at Imperial Hotel Osaka, in Japan on Monday, September 5, 2022. It was held by the planning of Council of Powder Technology, Japan and with the sponsorship of Hosokawa Micron Corporation. Nearly 180 people from the industries and universities attended this symposium. The theme of the symposium this year was "Frontiers of Powders and Powder Processing for SDGs". There were seven lectures including three special ones given by the 2019 KONA Awardee Prof. Makio Naito, 2020 KONA Awardee Prof. Brij M. Moudgil and 2022 Queen Elizabeth Prize winner Dr. Masato Sagawa. This 54th symposium was scheduled to be held two years ago, but due to the COVID-19 pandemic, this time it was held after three year interval in a hybrid style (on-site and online) for the first time.

Advances in nanotechnology have changed conventional concepts in materials science. This has also strongly influenced natural biomass products with hierarchically built-up structures. In general, hierarchical structures in bio-based materials are built up by molecular self-assembly, followed by nanoassembly to form higher-level structures. Key to each step is the formation of interactions at each individual scale. Nature usually achieves such fabrication through a bottom-up process. However, fabrication can also be achieved through a top-down process, with various such downsizing methods now in development. This review article aims to describe trends in nanofiber technology among downsizing processes applied to cellulose as a representative biomass, ranging from fundamentals to recent techniques. The advantages of our recently developed technique, nanopulverization by aqueous counter collision, are also discussed. This method successfully decomposes interactions selectively without damaging the molecular structure, finally liberating components of various sizes into water to provide a transparent and homogeneous component–water system. As nanocellulose research is a broad area involving various fields, the cited references are limited to the scope of the author’s knowledge.

Mathematical models of high-pressure grinding rolls (HPGR) have attracted great attention, owing to their role in optimization of operating machines as well as in the design and selection of new ones. Although population balance models (PBM) and the discrete element method (DEM) have been used in this task, both suffer from important limitations. Whereas PBMs have challenges associated to the prediction of operating gap and to the validity of several of its assumptions in different formulations in the literature, application of DEM has its own challenges, in particular when fed with distributions containing large amounts of fines. This work proposes a hybrid approach in which the coupling of DEM to particle replacement models and multibody dynamics is used to predict operating gap, throughput and power, as well as providing information along the rolls length that is used in PBM to predict the product fineness. The hybrid approach is then compared to both DEM and a PBM (Modified Torres and Casali), demonstrating similar results to the later when applied to simulating a pilot-scale machine operating under different conditions, but improved prediction when applied in scale-up to an industrial-scale HPGR.

A workflow for developing a multidimensional, linear correlation between the process conditions during fluidized bed spray granulation and the surface morphology of the resulting granules is presented. Spray coating experiments with Cellets®500 particles and sodium benzoate solution were performed in a lab-scale fluidized bed varying liquid spray rate, fluidization air flow rate, fluidization air temperature, spray air temperature and spray atomization pressure. To characterize the surface structure, the surface roughness of the coated particles was quantified using confocal laser-scanning microscopy. The roughness was correlated to the process conditions, and the resulting correlation was rigorously analyzed for the importance and co-linearities of the individual process parameters using a principal component analysis. The surface roughness is strongly dependent on the spray rate of the coating solution, the fluidization air temperature and the atomization pressure at the nozzle. In general, wet process conditions and large droplets with a low initial velocity favor the formation of particles with a rough surface structure, while dry conditions and fine droplets with a high velocity result in granules with a smooth and compact coating layer.

Nanoparticle synthesis using flow chemistry has the potential to enhance the large-scale accessibility of precision-engineered nanomaterials at lower prices. This goal has been difficult to achieve primarily due to reactor fouling and the lack of efficient reagent mixing encountered, especially in those scaled-up systems. The present study aimed to overcome the two challenges by integrating a liquid-liquid biphasic segmented flow system with static mixing. This strategy was applied to the synthesis of gold nanoparticles (AuNPs) using citrate reduction chemistry. It was demonstrated that reactor fouling was eliminated by implementing the biphasic flow strategy. As a result, the overall mean particle size of the as-synthesized AuNPs was measured to be 15.5 nm with a polydispersity index (PDI) of 0.07, and with the reproducibility of ± 6.4 %. The biphasic flow system achieved a reaction yield of 88.7 ± 1.1 % reliably with a throughput of 60 mL/hour up to 8 hours.

The properties of particle ensembles are defined by a complex multidimensional parameter space, namely particle size, shape, surface, structure, composition and their distributions. Macroscopic product properties are a direct result of these disperse particle properties. Therefore, the comprehensive multidimensional characterization of particle ensembles is a key task in any product design. However, the determination of complex property distributions is major challenge. We provide a broad overview of the current tools for multidimensional particle characterization. First, the mathematical handling of multidimensional (nD) property distribution is outlined as a necessary framework for the correct handling of nD particle size distributions (PSDs). Then, well-established techniques as well as recent developments with the potential to extract nD property distributions are reviewed. Ex situ imaging techniques like electron tomography or Raman spectroscopy with AFM co-localization, for instance, provide a resolution on the level of single particles but are limited in terms of sample statistics. A particular focus lies therefore on methods in the gas and the liquid phase, which provide multidimensional particle properties either directly or by a combination of one-dimensional techniques.